{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# OBP calculation for well"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "OBP calculation include the following step:\n",
    "\n",
    "1. Extrapolate density log to the surface\n",
    "2. Calculate Overburden Pressure\n",
    "\n",
    "\n",
    "- Calculate Hydrostatic Pressrue (*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {"nbsphinx": "hidden"},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(action='ignore')\n",
    "# for python 2 and 3 compatibility\n",
    "# from builtins import str\n",
    "# try:\n",
    "#     from pathlib import Path\n",
    "# except:\n",
    "#     from pathlib2 import Path\n",
    "#--------------------------------------------\n",
    "import sys\n",
    "ppath = \"../..\"\n",
    "\n",
    "if ppath not in sys.path:\n",
    "    sys.path.append(ppath)\n",
    "#---------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function, division, unicode_literals\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.style.use(['seaborn-paper', 'seaborn-whitegrid'])\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import pygeopressure as ppp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Extrapolate density log to the surface"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create survey with the example survey `CUG`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set to the directory on your computer\n",
    "SURVEY_FOLDER = \"M:/CUG_depth\"\n",
    "\n",
    "survey = ppp.Survey(SURVEY_FOLDER)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Retrieve well `CUG1`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "well_cug1 = survey.wells['CUG1']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get density log:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "den_log = well_cug1.get_log(\"Density\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "View density log:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xec7d748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_den, ax_den = plt.subplots()\n",
    "ax_den.invert_yaxis()\n",
    "\n",
    "den_log.plot(ax_den)\n",
    "\n",
    "# set style\n",
    "ax_den.set(ylim=(5000,0), aspect=(1.2/5000)*2)\n",
    "fig_den.set_figheight(8)\n",
    "fig_den.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Find optimized coefficients for Traugott equation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "a, b = ppp.optimize_traugott(\n",
    "    den_log, 2000, 3000, kb=well_cug1.kelly_bushing, wd=well_cug1.water_depth)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "View fitted density trend:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xec56b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_den, ax_den = plt.subplots()\n",
    "ax_den.invert_yaxis()\n",
    "# draw density log\n",
    "den_log.plot(ax_den, label='Density')\n",
    "# draw fitted density trend line\n",
    "den_trend = ppp.traugott_trend(\n",
    "    np.array(den_log.depth), a, b, \n",
    "    kb=well_cug1.kelly_bushing, wd=well_cug1.water_depth)\n",
    "\n",
    "ax_den.plot(den_trend, den_log.depth, \n",
    "            color='r', linestyle='--', zorder=2, label='Trend')\n",
    "\n",
    "# set style\n",
    "ax_den.set(ylim=(5000,0), aspect=(1.2/5000)*2)\n",
    "ax_den.legend()\n",
    "fig_den.set_figheight(8)\n",
    "fig_den.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we will extrapolate density to mudline (sea bottom), density values of the inverval from mudline to kelly bushing will be NaN (See figure above).\n",
    "\n",
    "Also, the actual variation of rock density underground doesnot have such high frequency as density logging data, so we need to perform some filtering and smoothing of the original signal."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Density log processing (filtering and smoothing):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "den_log_filter = ppp.upscale_log(den_log, freq=20)\n",
    "\n",
    "den_log_filter_smooth = ppp.smooth_log(den_log_filter, window=1501)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "View processed log data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xfaa9940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_den, ax_den = plt.subplots()\n",
    "ax_den.invert_yaxis()\n",
    "# draw density log\n",
    "den_log.plot(ax_den, label='Density')\n",
    "# draw fitted density trend line\n",
    "ax_den.plot(den_trend, den_log.depth, \n",
    "            color='r', linestyle='--', zorder=2, label='Trend')\n",
    "# draw processed density log\n",
    "ax_den.plot(den_log_filter_smooth.data, den_log_filter_smooth.depth,\n",
    "            color='g', zorder=3, label='Smoothed')\n",
    "\n",
    "# set style\n",
    "ax_den.set(ylim=(5000,0), aspect=(1.2/5000)*2)\n",
    "ax_den.legend()\n",
    "fig_den.set_figheight(8)\n",
    "fig_den.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extrapolate processed density log with fitted trend:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "extra_log = ppp.extrapolate_log_traugott(\n",
    "    den_log_filter_smooth, a, b, \n",
    "    kb=well_cug1.kelly_bushing, wd=well_cug1.water_depth)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "View extraploted density log:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1149f080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_den, ax_den = plt.subplots()\n",
    "ax_den.invert_yaxis()\n",
    "# draw density log\n",
    "den_log.plot(ax_den, label='Density')\n",
    "# draw trend line\n",
    "ax_den.plot(den_trend, den_log.depth, \n",
    "            color='r', linestyle='--', zorder=2, label='Trend')\n",
    "# draw processed density log\n",
    "ax_den.plot(den_log_filter_smooth.data, den_log_filter_smooth.depth,\n",
    "            color='g', zorder=3, label='Smoothed')\n",
    "# draw extrapolated density\n",
    "ax_den.plot(extra_log.data, extra_log.depth, \n",
    "            color='b', zorder=4, label='Extrapolated')\n",
    "\n",
    "# set style\n",
    "ax_den.set(ylim=(5000,0), aspect=(1.2/5000)*2)\n",
    "fig_den.set_figheight(8)\n",
    "fig_den.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The extrapolated log (blue line in the figure above) is used for calculation of Overburden Pressure."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Calculation of Overburden Pressure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "obp_log = ppp.obp_well(extra_log, \n",
    "         kb=well_cug1.kelly_bushing, wd=well_cug1.water_depth, \n",
    "         rho_w=1.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## * Calculation of Hydrostatic Pressure\n",
    "\n",
    "Since parameters used for hydrostatic pressrue calcualtion like kelly busshing and water depth are store in Well, so we add a shortcut for hydrostatic pressure calculation in Well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# hydro_log = ppp.hydrostatic_well(\n",
    "#     obp_log.depth, kb=well_cug1.kelly_bushing, wd=well_cug1.water_depth, \n",
    "#     rho_f=1., rho_w=1.)\n",
    "\n",
    "hydro_log = well_cug1.hydro_log()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "View calcualted overburden pressure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tFYkclUrc0Z2PZt5yf8ar7HPBBfDAA76uUiTtqVTierbpif3K+rrObt1g/XpvpK1IVKhU4mKxWO0vqocLLtBcthItKpVKOjTtwJqSNb6us3t3+OIL7ypmkShQqVQyvOtw3vviPd/Xq5n3JUpSMfF1YPRp14c+7fr4vt6DD4Y1a7ytlbw831cvkla0pZIi558PDz7oOoVI8qlUUqRHD1i9WsdWJPxUKimkK5glClQqKdS9O6xbp1G2Em4qlSr4Mb1kdTSXrYSdSqUKz33yHBt3bkzKugsLvXsEaXY4CSuVShWGFAxhwYoFSVv/hRfCvfcmbfUiTqlUqtCvQz/e+eKdpK2/c2fvuIruEyRhpFKpQqOMRuwt35vUz7joIpgxI6kfIeKESqUazbKbsaU0eTfx6dABdu2Cr75K2keIOKFSqcYPzA/Ysiu5dwabPFlbKxI+uvanGr3a9kr6Z7RrBxUV8OWX0LZt0j9OJCW0peLY5Mnwpz+5TiHiH5WKY23aQFaWN+eKSBioVNKAzgRJmKhU0kCrVt48K6tXu04i0nAqlVo88cETKfmcCy/U1oqEg0qlFh9/9TE79+xM+ue0aAEtW8JK/249JOKESqUWgzoNomh1UUo+a9IkXcEswadSqcUxXY7h9VWvp+SzmjWD/HxYtiwlHyeSFCqVWjTJbsL2Pam7G9ikSZodToJNpZKArIwsdpftTsln5eVBQQEUF6fk40R8p1JJwJSBU4iRnDsYVmXCBM28L8GlUklAfl4+WZlZKfu8xo2hTx94++2UfaSIb1Qqaeqcc+DRR12nEKk7lUqaatQIBg+GhQtdJxGpG5VKGhs9Gv76V296BJGgUKnUQXlFeUo/LyMDTjwR/vWvlH6sSIOoVOrghldvSPlnfv/78Nxz2lqR4FCp1FFZeVlKPy8Wgx/+EP72t5R+rEi9qVTqoO9BfXl/3fsp/9xhw2DBAihLbZ+J1ItKpQ6GFg5l/or5Tj77Jz+BOXOcfLRInahU6qBdk3as377eyWcfdRS8+y7sTs3VAiL1plKpo3ZN2jn77HHj4OGHnX28SEJUKnU0dfBUZ5992GHetAg7kz9nlEi9qVQCZuJETY0g6U2lEjAHHwzr18PWra6TiFRNpRJAul2qpDOVSgB16gSlpbq5u6QnlUo9lJWX8eGXHzrNMHky3HOP0wgiVVKp1ENmRiZzlrgdida2rTeZk25AJulGpVJPFVRQ4fgqP22tSDpSqdRT91bd+c/m/zjN0KwZdO6sSbIlvahU6um4wuOYt3ye6xicfz7MnOk6hcg3VCr1dHCrg/ls02euY5CdDQMGwOupud+ZSK1UKvUUi8U4odsJrmMA8OMfwxNPaCInSQ8qlQY4vtvxriMA3rSTo0bBs8+6TiKiUgmNESPg5Zc1kZO4p1IJkbFj4ZFHXKeQqFOphEi/ft7pZU2NIC6pVELmwgvhvvtcp5AoU6k00Prt63lx2YuuY3yte3fYuNH7JeKCSqWB8vPy02IQXGWXXAJ33eU6hUSVSqWBMmIZVJBeA0TatvWG8C9b5jqJRJFKxQf5efl8uf1L1zH2c9FFmshJ3FCp+GBowVAWrFzgOsZ+cnOhb19YtMh1EokalYoPjmh/BO9+8a7rGN+y7wZkGr4vqaRS8UFmRiaXDbrMdYxvyciAU0+FZ55xnUSiRKXik/y8fNcRqnT88d59mHVnQ0kVlUoEXHABPPig6xQSFSqVCOjdG1at0r2CJDVUKhExZQr86U+uU0gUqFR8VF5RTll5es490LEjlJfD2rWuk0jYNfJ7hcaYgcAt8cVzgXuBrcBEIAeYVd2ytTbQG+ivr3qdbbu38b0e33MdpUoXXwy//z3cdJPrJBJmvpcKcAjwPeC/gHeBoXjlcS5QCPwcaFzNcqCvWDmq41Hc8totaVsqLVpA+/bw0Udw6KGu00hY+b77Y619zFpbCgwAFltrPwCWAN2A9tbapTUsB1rjRo3ZXZbe524vuAAeeMB1CgmzpBxTMcYcAnQGlscfygSaAqU1LDdJRpZUy83KZceeHa5jVKtxY2/2/ddec51Ewirm9132jDG5wJ+B8cA4YAHe7s3xwDZgYXXL1tqbq1vv4sWLK/Ly8nzNmgyL1i+ivKKcI1scSU5Ojus4VSovh9/85iCuumodsdg3j5eWlqZt5qoELS8EM/OOHTvo379/rPZXepJxTOUqoC3ewdoFwDS8rZJJwC7g7hqWa9SrV68kxPVX1x5deXzp4+Tk5KR13vHj4eOPW3Paad88VlxcnNaZDxS0vBDMzIsXL67T630vFWvtdGB6pYcOnIp5bC3LgZablcv4I8dTnOb3Iv3ud+GKK7xbezRKxn8tElkapxJh48bBww+7TiFho1KJsL594bPPYPt210kkTFQqETd5sobvi79UKhFXUODdJ+jL9JoNUwJMpZIkn2z5JO0Hwu0zZYpm3xf/qFSSZPX21SxeU7dTca60bu39WrEiy3UUCQGVSpL0y+/HwpULXcdI2IUXwpNPtnIdQ0JApZIkzbObs2XXFtcxEpaTA4ccsot//9t1Egk6lUoSZcQy2Fu+13WMhI0atYVHH9Xs+9IwKpUkOrL9kbyz9h3XMRKWmemNsJ0713USCTKVShIN7zqc3Kxc1zHq5MQT4dVXYc8e10kkqFQqSdQqtxWHtTvMdYw605wr0hAqFfmWPn1g9WrYvNl1EgkilYpU6dJL4c47XaeQIFKpSJUOOgjy8uA//3GdRIJGpSLVuvhiuOce1ykkaFQqKTD7vdn4PW1nKuTmwhFHwBtvuE4iQaJSSYFGGY0o3pDeM8FV5+yz4fHHNSBOEqdSSYHjCo9j3vJ5rmPUS0YG/OhH8OSTrpNIUKhUUqBz886sLlntOka9HXccLFoEu3a5TiJBoFJJoSAeV9nnwgvh3ntdp5AgUKmkyCGtD+HTjZ+6jlFvPXvCxo2wYYPrJJLuVCop8uM+P6awZaHrGA2iAXGSCJVKiuRm5ZKdme06RoO0aeP9+vhj10kknalUpE4uvBDuu891CklnKhWpk8aNYdAgmBfMM+SSAioVqbPRo+Fvf/Nu9C5yIJVKiu3cs9N1hAaLxeCss2DOHNdJJB3VeGtuY0wvYAywC4gBmcBsa+1nKcgWSjcvuJlfffdXrmM02ODB8PTTcPrp3jVCIvtUu6VijBkNfA+Ybq29yVp7I3AT8GNjzH+lKmDYdGrWic+3fu46hi90y1SpSk1bKv+w1u4EMMYMBnrGH18NzE92sLDadx3QmL5jXEdpsG7dYMcOWLfOm39FBGrYUtlXKHFXHvBcadIShVzvtr0De8VyVS65RLdMlf3VeEylkjbAxcBOoAKYnbREIReLxVxH8FXLltCpE3zwgTe3rUiiZ3+KgfOAccD4pKWJiF75vdi+e7vrGL45/3yYOdN1CkkXiW6pZAG/xDsDVAFMSFqiCAjD8ZTKsrJg+HD417+8+wZJtNV09mesMeZoAGvteGvtBGvteOAxY8xpKUsogXDKKfCPf+gmZFLDloq19hFjzHhjzCi8Mz4xoCOwxFr7eKoCSjDEYjBxItx/vzdhtkRXjbs/1tqHAIwxrePLG1MRSoKpTx/4619h/Xpo1851GnEloQO11tqNKhRJxNSpcPvtrlOISwkdqDXG9AAGEy8ha61OKfugaHURAzsNdB3DVy1bQo8e8NZbMGCA6zTiQqKnlB8AmuAdVwnXQAuH5tq5riMkxXnnwezZuoo5qhI9pfwacL+1Vj8mPmrRuAWbSzfTMqel6yi+ysiAMWPgscdg7FjXaSTVatxSMca8Yox5GTgVWG6MeTm+LD4YUjCE11a+5jpGUgwaBB9+CFu2uE4iqVbb2Z/jUxUkigZ0HMD/LPwfRvYc6TpKUuw7aDt9uuskkkoJHVMxxpxZ6c+6ZbdPsjKz2F2223WMpGnfHlq1guLwXD8pCai1VIwxw4BTjDHHGWO+C3RPfqzoGNVzlOsISbXvJmQBvo+a1FEiWyrDgULgeOAY4JpkBoqawZ0Hu46QVNnZMHIk/O//uk4iqVLr2R9r7Q3GGKuh+VJfJ54IP/0pnHSSpp6MgkTHqSw2xvzeGHOLMUa7P1JnU6bAPToaFwmJlspNwGPA08AdyYsjYdW9O5SWwpo1rpNIsiVaKmutte8Ai4FwzNosKXfZZXCH/ksKvURL5XhjzGLg38BRGgDnr7LyMh5850HXMZKuWTPo1QsWLXKdRJIp0WH6R+GdSt4BfGGt1VQ8PsrMyGTZpmWuY6TE2LFw+eUwcKA3B4uET6JbKg8DNwJ9AM1GmgTZmdns2rvLdYyky8iAM8+EP//ZdRJJlkRLZTPwmbX2hWSGibKBnQby7zX/dh0jJY45Bt57D7aHZ+5vqSTRUvkKGGGMeQBYn8Q8kXVMl2NCe3FhVS69VPcLCqva7qX8HeA3QDawFSgAfp+CXJHTvHFzSnaXuI6RMl26eMdUVqyAwkLXacRPtW2p3AicZ609wVo7AvgJ3pgVSYKrh17tOkJK6e6G4VTb2Z8yIMcYU1DpsUR3maSO8rLyXEdIqbw86N8fFiyAoUNdpxG/1FYqW4AbDnhsa5KySASdeSZMm+YdvM3MdJ1G/FDbJE26xakkVSzmjV2ZPRvG66ctFLQrI84NGAAffwxbtQ0cCiqVNLO3fC879uxwHSPlpk7VdUFhoVJJM5tLN3Pf4vtcx0i59u2hSRP49FPXSaShVCppJj8vn692fOU6hhOTJ8Of/uQ6hTSUSiUNxWIxyiuid4ulnBwYMgRefNF1EmkIlUoa6tO2D0vXL3Udw4nTToO//x327nWdROpLpZKGhnUdxvwV813HcCIWg4kT4YEHXCeR+lKppKH2TdvTNLup6xjOHHYYrFsH63XpaiCpVNLUuCPGuY7g1NSpcNttrlNIfahUJC21bAk9e0JRkeskUlcqFUlb554Ljz4K5dE7ERZoKhVJWxkZXrHMmuU6idSFSkXS2oAB8NlnsGmT6ySSKJVKGlu2aRlrSnT3rWnTdNA2SFQqae75T553HcG5/Hzo2NGbLFvSn0oljXVr2S0y9wOqzQUXwMyZUFHhOonURqWSxmKxGDHdcQvwZoU780yYM8d1EqmNSiXNFbQoYMXmFa5jpIVjj4X334eS6Nx0IJBUKmluWGF0rwOqytSpcPvtrlNITRK9l7I40rNNT7bt3uY6Rtro0AGaN4ePPnKdRKqjLZU0F4vF6N+xv+sYaWXyZJgxQwdt05VKRQInKwtGjYIXX2zmOopUwffdH2NMC+B2vFulzgCuwrtX0EQgB5hV3bK1VvOpS0JGjIA//zmXHTu8m5JJ+kjGMZWjgGuBFsD7wOF45XEuUAj8HGhczbJugikJGzNmI3fe2YZf/tJ1EqnM990fa+2L8fVeCfzNWvsBsAToBrS31i6tYVkkYR077iUzE5ZpfGBaSdbZn6+AD4AJ8eVMoClQWsNyk9pWWlxc7G/KJCotLfU17z8//yf98/vTJqeNb+s8kN+Zk620tJQRIz7ixhvb8stfBmOauKB9j+sjGcdUfgS8CswBrjfG9MPb/VkJbDPG9Mfb3TlweVVt6+7Vq5ffcZOmuLjY17ylLUv5bNNnDOk1xLd1HsjvzMnm5T2U0aNh+fI2nHyy60S1C9r3GGDx4sV1en0ytlQ+AmYDO4EBwC/wtkomAbuAu2tYlmr0Pagvf/vob4zuPdp1lLQzahRccQV897vQuLHrNOJ7qcSPoYys9NDYA15S27JUITMjkwoNzKjWxRfDPffA5Ze7TiIapxIgrXJbsXHnRtcx0lKPHlBaCp9/7jqJqFQCZGjBUBasWOA6Rtq67DJdF5QOVCoB0r9jf0b2HFn7CyOqSRMYOBBeecV1kmhTqQRIRiyDRhm6BrQmo0fD//4v7NnjOkl0qVQkVGIxmDQJ7r/fdZLoUqlI6PTuDRs2eLdOldRTqUgo6bap7qhUAkinlWvXooW3xfLGG66TRI9KJYBmvDWD7bu3u46R9saMgccfh7Iy10miRaUSQMd0OYbXV73uOkbay8iAceP9XLiZAAARbklEQVTgoYdcJ4kWlUoADeo0iEWrF7mOEQhHHgkrVsBXX7lOEh0qlQDKzcqldG9p7S8UQLdNTTWVSkDlNMph556drmMEQps2UFAA77zjOkk0qFQCakT3EawuWe06RmBMmAAPP6wZ+FNBpRJQgzsPpkfrHq5jBEZmJpx1Fjz2mOsk4adSkcg4+mj44APYqns2JJVKRSJFB22TT6UikXLQQd6B2w8/dJ0kvFQqEjmTJsF99+mgbbKoVAJu3vJ5riMETlYWnHoqPPWU6yThpFIJuFeWv8Le8r2uYwTO8cdDURFs1yVUvlOpBFy/Dv14e+3brmME0mWXwR13uE4RPiqVgBtSMESTYddT587efYI+/dR1knBRqQRc69zWbCrd5DpGYE2Z4t0vSPyjUgmBjFgGZeWaNKQ+GjeGE0+EZ591nSQ8VCohcE7fc9hdttt1jMA6+WTvth6luvDbFyqVEOjZpie5WbmuYwTalClw992uU4SDSkUE6N4d9u6FlStdJwk+lYpI3KWXwp13uk4RfCoVkbi8PO9K5pdecp0k2FQqIpX88Ifw97/rtqkNoVIJkTsXadu9oWIxuOgimDHDdZLgUqmEyLrt66jQpbcNduihsHkzrF3rOkkwqVRCpGebnnz81ceuY4TC1Klw++2uUwSTSiVEhhUOY94KTYXgh+bNoW9feO0110mCR6USIoUtC1m5RQMt/HL22fDEE7ptal2pVEImI6a/Ur/EYt6tPR54wHWSYNFPYMhcN+w61xFC5TvfgS++8H5JYlQqIZOZkek6Quhcfrlm4K8LlYpILZo3h3794NVXXScJBpWKSALOOAOeeQZ2a4aJWqlURBIQi8HFF2t6hESoVEKovKKcL7d/6TpG6PTs6W2prFjhOkl6U6mEUIwYty/ScNBkuOwyjbStjUolhGKxmOsIoZWb681pO3eu6yTpS6USUh2admBtia6IS4aTT4b583UjsuqoVELquMLjmL9ivusYoaULDqunUgmpPu36sHT9UtcxQqtLF2jaFIqLXSdJPyqVkMqIZXBYu8Ncxwi1yZO9yZw0hc3+VCohduZhZ7qOEGpZWd6guDlzXCdJLyoVkQYYMgSWLPFmihOPSkWkga64Av74R9cp0odKRaSB2raFggJYvNh1kvSgUhHxwfjxMGuWZokDlUrofbXjK95e+7brGKGXkeEVy4MPuk7inkol5Jo3bs5cqzHlqXDkkbB6Naxb5zqJWyqVkMvKzGJv+V7XMSJDB21VKpHQNLspJbtKXMeIhObN4YgjYF6E75SiUomAY7scy2urdAObVDnzTHj66ejOEqdSiYCBnQZStLrIdYzIiMVgyhS45x7XSdxQqURA40aNGd17tOsYkdKzJ5SWRnOWOJVKRPRu29t1hMiZOhXuuMN1itRTqYgkSW4unHACPPus6ySppVIRSaLvfx9eeQV27HCdJHVUKiJJFrVZ4lQqIklWUAB5efDRR66TpIZKJUIWfb6I11ZqvIoLF18Mf/pTNGaJU6lESJ92fViwcoHrGJGUlQWjR8NzzzV3HSXpVCoR0jS7Kdt2b3MdI7KGDgVrG7Nli+skyaVSiZisjCx2l0V0/HgaOO+8jaG/4FClEjEDOg5g8RpNUeZKmzZldO4Mb4d4ihuVSsQMKRjCm5+/6TpGpI0fDw89FN5Z4lQqEdMipwXTBk9zHSPSMjPDPUucSiWCdAN39/r1g88/h/XrXSfxn0pFxJErroBbb3Wdwn8qFRFHWrSA73wH5s93ncRfKhURh846C556KlyzxKlUImptyVrKykN6+iFA9s0Sd9ddrpP4R6USUQtXLmTJ+iWuYwjeLHFlZfDZZ66T+EOlElFDC4cyf0XIduYD7LLLvFniwnDBoUoloto3bc/67SE8nxlQjRvDD38If/mL6yQNp1KJuIow/NcYEsOHw7vvwubNrpM0TKNkrdgY8yTwO+AGYCswEcgBZlW3bK3dmqw88m292/ameEOxJsVOIz/7GfzhD3DTTa6T1F9SSsUYMwI4CvgZ8HOgMXAuUFjLcoiOgae/47sez/LNy13HkEry86FHD3jjDTj6aNdp6sf33R9jTCNgHN4WyC5r7VJgCdANaF/LsqRQh2YdOLpLQH9yQ+zcc2HOHNizx3WS+knGlsolwB3AyUCH+GOZQFOgtIblJrWtuLi42NegyVRaWhqovBC8zEHLC4lnPumkbKZPb8K5525KQSp/JaNUjgAKgKOBAcaYfnjHTlYC24wx/fF2dw5cXlXbinv16pWEuMlRXFwcqLwQvMxBywuJZ+7VC5YuhZyc9nRzvA2/eHHd5t/xvVSsteMAjDHTgUnAL/C2SiYBu4C7a1gWkbipU+HKK+GPf/RG3gZF0s7+WGtvjP9x7AFP1bYsIkBODowa5V0bNDpAt8LWOBXh+U+e13iVNDViBPz73wRqsmyVirC6ZLVOLaexn/7UG7sSFCoVYVjhMF0HlMbatYOuXaGoyHWSxKhUhB6te/Dpxk9dx5AajBsHjzwCe/e6TlI7lYpoztoAyMiAiy7ybp2a7lQqAkCn5p34YscXrmNIDfr0gZISWLHCdZKaqVQEgNG9R5PbKNd1DKnFtGlw223pPe+KSkUAyM/Lp0V2C9cxpBZ5efC978Ezz7hOUj2VikjAnHQSvP66tyuUjlQqIgGUzmNXVCoiAdS+PXTqBHW81i8lVCoiAXX++fDww+k3dkWlIvv57cLfuo4gCcrIgIkT4d57XSfZn0pF9pOdmc2GHRtcx5AE9e0LmzZ5N3tPFyoV2c/QwqEsXLnQdQypg8sv9+ZcSRcqFdnPEe2P4J2177iOIXXQpIl3e49//MN1Eo9KRfbTKKMRZRW6x3LQnHIKvPwy7NjhOolKRaqQn5fP9t3bXceQOpo2LT12g1Qq8i3TBk+jSXatNzeQNNOlCzRvDh984DaHSkUkRCZPhhkzoLzcXQaVikiINGoEY8Z4Ezq5olIRCZnBg+GTT2CDo+FGKhWREPrpT+HWW918tkpFqqUZ9oOrVSs47DCY72A+c5WKVGvm2zNdR5AGOPts+OtfYffu1H6uSkWqldMohx170mA0ldRLLAZTpsDdd6f2c1UqUq3BnQfz5udvuo4hDWCMt6Xyn/+k7jNVKlKto7sczRur3nAdQxpo6lS4447UTZatUpFq5WXlsXPvTtcxpIFycuD734enn07N56lUpEYDOw10HUF8cOKJ8OabqZksW6UiNfqB+YHrCOKTVI1dUamIRET79t6vd5I8XY5KRSRCLrgAHnwQypI4ZY5KRSRCMjNhwgSYmcRxjSoVkYg58khYuxa++CI561epSK3KK8p59uNnXccQH11xRfIO2qpUpFYZsQwNgguZZs1g0CD417/8X7dKRRKSmZFJWbkmxA6T00+H556D0lJ/16tSkYQc0f4I3v3iXdcxxEexGFx6Kdx5p7/rValIQo4rPI4FKxe4jiE+697d+33ZMv/WqVKRhOTn5fPVjq9cx5AkuPRSmDPHv/WpVCRh5/c733UESYKcHPjv//ZvfSoVSVjXll1dR5AAUKmIiK9UKiLiK5WKiPhKpSIivlKpiIivVCoi4iuVioj4SqUiIr5SqYiIr1QqIuIrlYqI+EqlIiK+UqmIiK9UKiLiK5WKiPhKpSIivlKpiIivVCoi4iuVioj4SqUiIr5SqYiIr1QqIuIrlYqI+EqlIiK+UqmIiK9UKiLiK5WKiPhKpSIivlKpiIivVCoi4iuVioj4SqUiIr5SqYiIr1QqIuIrlYqI+EqlIiK+UqmIiK9UKiLiK5WKiPiqkd8rNMYMAq4DlgMPAzcAW4GJQA4wq7pla+1Wv/OISGr5XirAEcDPrbUfGGN+B/wcaAycCxTWsnxXEvKISAolY/fnSOByY8wzwBHW2qXAEqAb0L6WZREJuGRsqfzMWrstvhu0MP5YJtAUKK1huUltK168eLHPUZMraHkheJmDlheCmbkuklEqPwHuA1oD040x/fF2b1YC22pYXlXTSvv37x9LQlYR8VkySqU0vuuzF7gc+DXeVskkYBdwdw3LIhJwsYqKCtcZRCRENE5FRHylUhERXyXjmIqvjDHtCMAAOWPMQOCW+OK5wL2keeZ9jDFPAr+j0kDFdM5sjDkMOAe4lTT/2YifBZ2Kd3bzUtL858IYMxZoCfyFeg5UTftSwRscF4QBcocA3wP+C3gXGIr3F5HOmTHGjACOAn5GML7PANcD5wPXkP6ZxwBTgL7AO8BxpOnPhTGmLzAMeJ9v/7tLeKBqEHZ/AjFAzlr7mLW2FBgALLbWfkCaZzbGNALG4f0PtCsI32djzGigN/AQ0D0Amf8P7x/gZcAL6fxzYa19H5gNxGjAQNUglEqdBsi5ZIw5BOiMd90TpH/mS4A7gHKgQ/yxdM/8E+BkvE3yVvHH0jnzYLxdib8CR8cfS+e8+8aD1XugahB2f5YmOkDOJWNMLt4xlfHAuCBkxrtOqwDvh32AMaYf3qZ5OmfeBKzG+972D0Dmw4CbgObAPQHIu8/S+g5UDUKpPEQwBshdBbTFK5YFwDTSPLO1dhyAMWY6Xs5fkOaZgRnAI0AzYBTeAMt0zvww8Cre1uAPSP+8ABV4/+7uoR4DVTX4TUR8FYRjKiISICoVEfGVSkVEfKVSERFfqVRExFcqFYkEY8zxxpiO9XzvuX7nCTOdUk5DxpgCvDEBFcA91toX6vj+QuB6a+34en7+eUCFtXZ2Pd87CW/A1BZr7UX1yeAnY0xbvHFD9wH/AdrgXTzZDG/087HAFuADa+31Vbz/WKCntfahFEUONG2ppKdpwLXAD/EGS9WHy/8t7rXWng3siV9R7Np44LfxP+/Eu7ivJ973qAL4lbX2DKCfMabZgW+21r6Gd8GoJCAII2qjqCfwobW2zBiTZYy5zVo7zRhzB97l/t3wrn5tDfzWWrvIGPMm8DbeFdL/Bww0xtwHtMCbJuA+4Dpr7UpjzCvW2uONMa8CbwJbrbW/Nsb8Gu8aoC7AbGNMJ7wh5pnAG8DzwJPA08AJwBnW2s01fB3N8YZ3X4e3VdAZuBBvVObX67XWzjDGzMS7viTXWjvBGPMj4HQgD7gS7xqaCmvt7Er5H8LbIjrYWnuOMeZwvBJuAjxmrZ0bz5Fjrd1qjGkFvAd8ByirIm82sDv+fegM5AI/sdbuAT43xrSy1m6q4esVtKWSrsr55sKucqCTMSYL6GitXY53s7Yvgc/55iK1Q/BK47748kpr7STgLbzpGCpvuez7c0fg4XihNAMOj+8yvRR//tL4a1cDg+KP7bTW/gYowruupSoTjTGzgaJ4XvCugj7LWrulmvUavOHsv4sv9wKWAb+Jf52VVf5aPrfWnhP/838Dm/GK5phKr6k8afqneIW4otJzVxljHgVmWmt34ZXyC3iX+/eMvy4Dt1t/gaEtlfT0EXCYMeZ9YA/eP/IbgBfjz5fhzSnSCm+qBYD3rbVfVlpHxQG/lwNZxpiDK71mtbX2o/ifY8Du+J93xZcrgIestQuNMRfEn/ss/vtuqv9P6f4qjsf83wHZvl6vMSYTb5evFTDTGHMiMDe+/knA6/H82caYGNC9hvXeCmwAflTp8ZL4Vgp437t2wHPEt36A/7HWzgcwxjTBK7JfAovwtqYAOtWyVSZx2lJJT3fibY38FfgD8ARwMd4l9AA3A3PwZhFbG3/swP9Fuxpj7gcGAv8EXgauBs6o9Jqv3xOfyavYGPN7YGT8ubuAK4wxT+D9o6aq9ybgwNfeXXm91toy4CK83Z01eMc9jsTboumIt3VRFH/+qvjzVa33f/C+d3OAjZUefwjva9/n/fivqr6G3cBXwKl437tW8Yms3kvwa408nf2RejPGdMC78raCb7ZsHrTW7nUarArGmKPwdpXW1vrib7/3h9bavyUhViipVETEV9r9ERFfqVRExFcqFRHxlUpFRHylUhERX6lURMRX/w9hTZnVnT6wCgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12cfdb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_obp, ax_obp = plt.subplots()\n",
    "ax_obp.invert_yaxis()\n",
    "\n",
    "hydro_log.plot(ax_obp, color='g', linestyle='--', label='Hydrostatic')\n",
    "\n",
    "obp_log.plot(ax_obp, color='b', label='OBP')\n",
    "\n",
    "# set style\n",
    "ax_obp.set(ylim=(5000,0), aspect=(100/5000)*2)\n",
    "ax_obp.legend()\n",
    "fig_obp.set_figheight(8)\n",
    "fig_obp.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save calculated Overburden Pressure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# well_cug1.add_log(\"Overbuden_Pressure\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*optional, calculated overburden pressure has already been saved, so users don't need to run these notebooks in specific order.*"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
